Learn Data Science – Do Programming using Python & R

Course Name: – Learn Data Science – Do Programming using Python & R

Date & Time: – Sat 03th Aug to Sat 31st Aug 2019 every Saturday from 5:30 PM to 9:30 PM

Cost: –

Booking between 07 July to 20 July 2019 – 1000 INR discount, you pay 13000 INR
Booking between 21 July to 27 July 2019 – 500 INR discount, you pay 13500 INR
Booking between 28 July to 02 Aug 2019 – 0 INR discount, you pay 14000 INR

Good news for enrolled candidates of Data Science training where they will get chance to attend FREE sessions on Mathematics which are pre-requisite required to accomplish Data Science training, see syllabus and other details here

Key Features

No PPT’s completely Hands-on Data Science – R programming training.

For MAC system download link of Python, NumPy, SciPy & matplotlib get from here

All at only 14000 INR

What is Data Science?

Why to choose Data Science as career?

Python basics

1) Introduction
2) Data types and operator
3) List tuples and dictionaries
4) Object oriented
5) Exceptions handling
6) File handling
7) Modules

NumPy

Introduction
Environment
Ndarray Object
Data Types
Array Attributes
Array Creation Routines
Array from Existing Data
Array From Numerical Ranges
Indexing
Slicing
Broadcasting
Array Manipulation
Binary Operators
String Functions
Mathematical Functions
Arithmetic Operations
Statistical Functions
Sort, Search & Counting Functions
Byte Swapping
Copies & Views
Matrix Library
Linear Algebra
I/O with NumPy

Python Pandas

Introduction
Data Structures
Series
DataFrame
Panel
Basic Functionality
Descriptive Statistics
Function Application
Reindexing
Iteration
Sorting
Text Data
Options
Customization
Indexing
Selecting Data
Statistical Functions
Window Functions
Aggregations
Missing Data
GroupBy
Merging/Joining
Concatenation
Date Functionality
Timedelta
Categorical Data
Visualization
IO Tools
Sparse Data

Data Loading, Storage, and File Formats

Reading and Writing Data in Text Format
Reading Text Files in Pieces
Writing Data Out to Text Format
Manually Working with Delimited Formats
JSON Data
XML and HTML: Web Scraping

matplotlib API

Figures and Subplots
Colors, Markers, and Line Styles
Ticks, Labels, and Legends
Subplot
Saving Plots to File
matplotlib Configuration
Plotting Functions in pandas
Line Plots
Bar Plots
Histograms and Density Plots
Scatter Plots
Python Visualization Tool Ecosystem

R Programming
if statements
for statements
while statements
repeat statements
break and next statements
switch statement
scan statement
Executing the commands in a File
Data structures
Vector
Matrix
Array
Data frame
List